[Bug] Can not spesify partiual column when load

### Search before asking

- [x] I had searched in the [issues](https://github.com/apache/incubator-doris/issues?q=is%3Aissue) and found no similar issues.

### Version

25.2

### What's Wrong?

Implicitly specifying columns when writing data to Doris will trigger a schema validation error.

### What You Expected?

No error

### How to Reproduce?

```
CREATE TABLE `ail` (
`k_id` bigint NOT NULL DEFAULT "0" COMMENT "xxx",
`o_no` varchar(64) NOT NULL DEFAULT "" COMMENT "xx",
`i_in` int NOT NULL DEFAULT "0" COMMENT "xx",
`s_id` bigint NOT NULL DEFAULT "0" COMMENT "xx",
`s_tt` int NOT NULL DEFAULT "0" COMMENT "xxx",
`id` bigint NOT NULL AUTO_INCREMENT(1) COMMENT "xxx"
) ENGINE=OLAP
UNIQUE KEY(`k_id`, `o_no`, `i_in`, `s_id`, `s_tt`)
```
pyspark code:
```
import logging
import sys
from pyspark.sql import SparkSession

def log(message):
"""自定义日志函数，强制刷新输出"""
print(message)
sys.stdout.flush()

def create_spark_session(app_name="Doris_Data_Ingestion"):
"""创建SparkSession"""

spark = SparkSession.builder \
.appName(app_name) \
.getOrCreate()
return spark

def validate_source_data(spark, source_table):
"""验证源表数据"""

try:
# 检查源表是否存在
spark.sql("select * from mock_source").show()
except Exception as e:
print(f"验证源表数据失败: {str(e)}")
return False
source_df = spark.sql("select k_id from mock_source")
source_df.printSchema()
write_df = source_df.write \
.format("doris") \
.option("doris.table.identifier", "test.ail") \
.option("doris.fenodes", "127.0.0.1:8030") \
.option("user", "admin") \
.option("password", "xxxxxxxx") \
.option("doris.sink.batch.size", "500000") \
.option("doris.sink.batch.interval.ms", "15000") \
.option("doris.sink.max-retries", "3") \
.option("doris.write.fields", "k_id") \
.option("doris.read.field", "k_id") \
.mode("append")
# .option("mergeSchema", "true") \
# .option("columnMapping", "k_id") \
write_df.save()

def create_doris_temp_view(spark):
"""创建Doris临时视图"""

try:
# 创建Doris临时视图
spark.sql("""
CREATE TEMPORARY VIEW mock_source
AS SELECT 1 AS k_id
""")
return True
except Exception as e:
print(f"创建Doris临时视图失败: {str(e)}")
return False

def main():
log("=" * 60)
print("\n步骤1: 创建 spark sessioin...")
spark = create_spark_session()
# spark.sparkContext.setLogLevel("DEBUG")
print("\n步骤2: 创建临时视图")
create_doris_temp_view(spark)
print("\n步骤3: 验证源表数据...")
if not validate_source_data(spark, 'test.ail'):
spark.stop()
return

if __name__ == "__main__":
main()
```
Use spark connector 25.2
`spark-submit --master local --jars spark-doris-connector-spark-3.5-25.2.0.jar t1.py`
error message:
```
2026-04-15 15:15:40,216 [INFO] [dispatcher-BlockManagerMaster] BlockManagerInfo: Removed broadcast_0_piece0 on 9.0.16.20:38273 in memory (size: 3.7 KiB, free: 434.4 MiB)
Traceback (most recent call last):
File "/data/t1.py", line 75, in
main()
File "/data/t1.py", line 69, in main
if not validate_source_data(spark, 'test.ail'):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/t1.py", line 44, in validate_source_data
write_df.save()
File "/data/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 966, in save
File "/data/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
File "/data/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 196, in deco
pyspark.sql.utils.AnalysisException: Cannot write incompatible data to table 'test.ail':
- Cannot find data for output column 'o_no'
- Cannot find data for output column 'i_in'
- Cannot find data for output column 's_id'
- Cannot find data for output column 's_tt'
- Cannot find data for output column 'id'
```
Spark connector 1.3.2 is ok.

### Anything Else?

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [x] I agree to follow this project's [Code of Conduct](https://www.apache.org/foundation/policies/conduct)

Start at the Spark connector 25.2 write path reached by write_df.save() and trace the schema validation that reports missing output columns. Compare its behavior with connector 1.3.2 using the supplied partial-column reproduction; done means writing only k_id succeeds without errors for the shown Doris table.

Written by the indexing model from the issue text.